Part IV: The Next Paradigm

Chapter 14 — The Falsification Program: A Framework for Testing Informational Phase Space Cosmology

Integrating all experimental regimes into a coherent empirical roadmap

The scientific validity of any cosmological theory rests on its falsifiability. For Informational Phase Space Cosmology (IPSC), this requirement is not philosophical ornament but operational necessity. A theory claiming that information is ontologically primary must be testable in the laboratory, the biosphere, and the cosmos alike. This chapter consolidates all prior proposals into a single, quantitative Falsification Program — a unified empirical framework structured to challenge IPSC’s predictions across three scales and five methodological domains.

1. Overview and Guiding Principles

IPSC’s falsification framework rests on three guiding principles:

Multi-Scale Consistency: Predictions must cohere across quantum, mesoscopic, and cosmic regimes; informational curvature cannot appear only locally or only globally.
Quantifiable Metrics: Every experiment must yield measurable quantities expressible in the same informational units — primarily Fisher information (F), mutual information (I), and informational curvature (R^(info)).
Cross-Domain Correlation: Independent verification across distinct physical domains is required to confirm universality. A single confirmed signal is suggestive; correlated signals across regimes are decisive.

Under these conditions, IPSC becomes an experimentally tractable cosmological hypothesis rather than a philosophical conjecture.

2. Consolidated Predictive Matrix

The table below summarizes IPSC’s quantitative predictions across scales:

Domain	Primary Observable	Predicted IPSC Signature	Classical/Standard Expectation	Validation Criterion
Quantum	Coherence lifetime (T₂) vs. informational density	T₂ ∝ F^α with α ≈ 0.5–1	No dependence on information topology	Correlation coefficient R > 0.8
Molecular	Entropy production under feedback	⟨σ⟩ < k_Bln2 per bit erased	⟨σ⟩ ≥ k_Bln2	≥3σ deviation from Landauer bound
Neural	Fisher curvature vs. synchronization	Peak F precedes global phase-locking	Random or task-dependent variance	Predictive curvature rise confirmed
Artificial	Curvature during learning	Phase transition at generalization onset	Smooth or linear curvature increase	Critical inflection in F vs. accuracy curve
Cosmic	CMB E–B mutual information	I(E;B) ≠ 0 at ℓ ≈ 20–40	I(E;B) ≈ 0	Persistent nonzero signal >2σ
Cosmic	Fractal clustering dimension D₂	D₂ = 2.95 ± 0.02	D₂ = 3	Deviation confirmed across surveys
Cosmic	Global vorticity (ω₀)	ω₀ ≈ 10⁻¹⁷ s⁻¹	ω₀ = 0	Consistent preferred-axis alignment

This predictive matrix provides the empirical backbone of the falsification program: each row represents a distinct avenue by which IPSC can be disproven. If data fail to exhibit the predicted informational dependencies, the hypothesis that information is the primary substrate collapses.

3. Statistical Framework for Cross-Scale Verification

To prevent isolated anomalies from masquerading as confirmation, IPSC’s testing program adopts a multi-domain Bayesian validation model. For each experimental regime, the posterior probability of the theory (P_IPSC) is updated according to:

P_IPSC ∝ Π_i [P(D_i|H_IPSC) / P(D_i|H₀)]

where D_i are data from independent domains (quantum, neural, cosmological), and H₀ is the null hypothesis (no informational curvature). A composite Bayes factor >10 (strong evidence) across three domains would justify acceptance; a factor <1/10 would falsify the model.

Operational Rule: IPSC is considered empirically falsified if at least two independent experimental classes yield null or contrary results at ≥95% confidence.

4. Experimental Timeline and Infrastructure

The falsification program can proceed in three parallel phases:

Phase I (0–5 years): Laboratory and Computational Validation

Quantum coherence experiments with biological NV-center systems.
Microfluidic feedback thermodynamics.
Neural and AI curvature analysis using existing datasets.
Development of open-source IPSC simulation frameworks.

Phase II (5–10 years): Integrated Cross-Disciplinary Trials

Establish multi-institutional “Informational Geometry Laboratory” linking quantum biology, neuroscience, and cosmology groups.
Deploy joint statistical pipeline for Fisher metric estimation across disciplines.
Publish annual “Informational Curvature Index” comparing observed vs. predicted curvature trends.

Phase III (10–20 years): Astronomical Verification

High-resolution CMB polarization and quasar rotation studies (LiteBIRD, SKA, LISA).
Integration with gravitational-wave anisotropy data.
Comprehensive Bayesian synthesis of all domains.

5. Decision Criteria and Interpretation

IPSC’s strength lies in its vulnerability: it risks falsification from multiple angles. Confirming results in any one domain must be accompanied by corresponding curvature trends elsewhere. Conversely, a consistent absence of predicted correlations across domains would falsify IPSC outright. The theory’s explanatory appeal does not exempt it from experimental accountability.

Should IPSC survive such scrutiny, its consequences would extend beyond physics. It would imply that meaning, coherence, and self-reference are not epiphenomena but structural aspects of nature. If falsified, the experiment would still clarify the limits of information-theoretic models of reality — a valuable contribution in itself.

Philosophical Implication: The decisive test of IPSC is not whether the universe “is” informational, but whether the dynamics of information suffice to reproduce all measurable structure without remainder.

The next chapter returns to the reflective register of *Meaning Matters* — addressing the ethical and philosophical implications of a universe that learns, remembers, and possibly thinks. Chapter 15 — Ethics of a Thinking Universe begins that final inquiry.